Search (47 results, page 1 of 3)

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Abstract

XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced with the problem of semantic interoperability. In this paper we discuss why this problem is not solved by XML, and then discuss why the Resource Description Framework is only a partial solution. We then present the SHOE language, which we feel has many of the features necessary to enable a semantic web, and describe an existing set of tools that make it easy to use the language.

Date

11. 5.2013 19:22:18

Type

a

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Date

22. 9.2007 15:41:14

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Date

22. 9.2007 15:41:14

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Date

22. 9.2007 15:41:14

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Date

14. 8.2011 13:33:22

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Abstract

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.

Content

Vgl. unter: http://www.dblab.ntua.gr/~bikakis/LD/5.pdf Vgl. auch: http://swoogle.umbc.edu/. Vgl. auch: http://ebiquity.umbc.edu/paper/html/id/183/. Vgl. auch: Radhakrishnan, A.: Swoogle : An Engine for the Semantic Web unter: http://www.searchenginejournal.com/swoogle-an-engine-for-the-semantic-web/5469/.

Type

a

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Abstract

In this talk we present a retrieval model based on social ontologies. More specifically, we utilize the Wikipedia category system in order to perform semantic searches. That is, textual input is used to build queries by means of which documents are retrieved which do not necessarily contain any query term but are semantically related to the input text by virtue of their content. We present a desktop which utilizes this search facility in a web-based environment - the so called eHumanities Desktop.

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Content

"Textual content-based search engines for the web have a number of limitations. Firstly, many web resources have little or no textual content (images, audio or video streams etc.) Secondly, precision is low where natural language terms have overloaded meaning (e.g. 'bank', 'watch', 'chip' etc.) Thirdly, recall is incomplete where the search does not take account of synonyms or quasi-synonyms. Fourthly, there is no basis for assisting a user in modifying (expanding, refining, translating) a search based on the meaning of the original search. Fifthly, there is no basis for searching across natural languages, or framing search queries in terms of symbolic languages. The Semantic Web is a framework for creating, managing, publishing and searching semantically rich metadata for web resources. Annotating web resources with precise and meaningful statements about conceptual aspects of their content provides a basis for overcoming all of the limitations of textual content-based search engines listed above. Creating this type of metadata requires that metadata generators are able to refer to shared repositories of meaning: 'vocabularies' of concepts that are common to a community, and describe the domain of interest for that community.
This type of effort is common in the digital library community, where a group of experts will interact with a user community to create a thesaurus for a specific domain (e.g. the Art & Architecture Thesaurus AAT AAT) or an overarching classification scheme (e.g. the Dewey Decimal Classification). A similar type of activity is being undertaken more recently in a less centralised manner by web communities, producing for example the DMOZ web directory DMOZ, or the Topic Exchange for weblog topics Topic Exchange. The web, including the semantic web, provides a medium within which communities can interact and collaboratively build and use vocabularies of concepts. A simple language is required that allows these communities to express the structure and content of their vocabularies in a machine-understandable way, enabling exchange and reuse. The Resource Description Framework (RDF) is an ideal language for making statements about web resources and publishing metadata. However, RDF provides only the low level semantics required to form metadata statements. RDF vocabularies must be built on top of RDF to support the expression of more specific types of information within metadata. Ontology languages such as OWL OWL add a layer of expressive power to RDF, and provide powerful tools for defining complex conceptual structures, which can be used to generate rich metadata. However, the class-oriented, logically precise modelling required to construct useful web ontologies is demanding in terms of expertise, effort, and therefore cost. In many cases this type of modelling may be superfluous or unsuited to requirements. Therefore there is a need for a language for expressing vocabularies of concepts for use in semantically rich metadata, that is powerful enough to support semantically enhanced search, but simple enough to be undemanding in terms of the cost and expertise required to use it."

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Abstract

Currently, a number of efforts are being carried out to integrate collections from different institutions and containing heterogeneous material. Examples of such projects are The European Library [1] and the Memory of the Netherlands [2]. A crucial point for the success of these is the availability to provide a unified access on top of the different collections, e.g. using one single vocabulary for querying or browsing the objects they contain. This is made difficult by the fact that the objects from different collections are often described using different vocabularies - thesauri, classification schemes - and are therefore not interoperable at the semantic level. To solve this problem, one can turn to semantic links - mappings - between the elements of the different vocabularies. If one knows that a concept C from a vocabulary V is semantically equivalent to a concept to a concept D from vocabulary W, then an appropriate search engine can return all the objects that were indexed against D for a query for objects described using C. We thus have an access to other collections, using a single one vocabulary. This is however an ideal situation, and hard alignment work is required to reach it. Several projects in the past have tried to implement such a solution, like MACS [3] and Renardus [4]. They have demonstrated very interesting results, but also highlighted the difficulty of aligning manually all the different vocabularies involved in practical cases, which sometimes contain hundreds of thousands of concepts. To alleviate this problem, a number of tools have been proposed in order to provide with candidate mappings between two input vocabularies, making alignment a (semi-) automatic task. Recently, the Semantic Web community has produced a lot of these alignment tools'. Several techniques are found, depending on the material they exploit: labels of concepts, structure of vocabularies, collection objects and external knowledge sources. Throughout our presentation, we will present a concrete heterogeneity case where alignment techniques have been applied to build a (pilot) browser, developed in the context of the STITCH project [5]. This browser enables a unified access to two collections of illuminated manuscripts, using the description vocabulary used in the first collection, Mandragore [6], or the one used by the second, Iconclass [7]. In our talk, we will also make the point for using unified representations the vocabulary semantic and lexical information. Additionally to ease the use of the alignment tools that have these vocabularies as input, turning to a standard representation format helps designing applications that are more generic, like the browser we demonstrate. We give pointers to SKOS [8], an open and web-enabled format currently developed by the Semantic Web community.

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Abstract

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.

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Abstract

This description of OWL, the Web Ontology Language being designed by the W3C Web Ontology Working Group, contains a high-level abstract syntax for both OWL DL and OWL Lite, sublanguages of OWL. A model-theoretic semantics is given to provide a formal meaning for OWL ontologies written in this abstract syntax. A model-theoretic semantics in the form of an extension to the RDF semantics is also given to provide a formal meaning for OWL ontologies as RDF graphs (OWL Full). A mapping from the abstract syntax to RDF graphs is given and the two model theories are shown to have the same consequences on OWL ontologies that can be written in the abstract syntax.

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Abstract

This document defines the Simple Knowledge Organization System (SKOS), a common data model for sharing and linking knowledge organization systems via the Web. Many knowledge organization systems, such as thesauri, taxonomies, classification schemes and subject heading systems, share a similar structure, and are used in similar applications. SKOS captures much of this similarity and makes it explicit, to enable data and technology sharing across diverse applications. The SKOS data model provides a standard, low-cost migration path for porting existing knowledge organization systems to the Semantic Web. SKOS also provides a lightweight, intuitive language for developing and sharing new knowledge organization systems. It may be used on its own, or in combination with formal knowledge representation languages such as the Web Ontology language (OWL). This document is the normative specification of the Simple Knowledge Organization System. It is intended for readers who are involved in the design and implementation of information systems, and who already have a good understanding of Semantic Web technology, especially RDF and OWL. For an informative guide to using SKOS, see the [SKOS-PRIMER].

Editor

Miles, A. u. S. Bechhofer

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Abstract

This is a specification of a precise semantics, and corresponding complete systems of inference rules, for the Resource Description Framework (RDF) and RDF Schema (RDFS).

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Abstract

This document provides a tutorial on how to publish Linked Data on the Web. After a general overview of the concept of Linked Data, we describe several practical recipes for publishing information as Linked Data on the Web.

Content

This tutorial has been superseeded by the book Linked Data: Evolving the Web into a Global Data Space written by Tom Heath and Christian Bizer. This tutorial was published in 2007 and is still online for historical reasons. The Linked Data book was published in 2011 and provides a more detailed and up-to-date introduction into Linked Data.

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Abstract

The Web Ontology Language OWL is a semantic markup language for publishing and sharing ontologies on the World Wide Web. OWL is developed as a vocabulary extension of RDF (the Resource Description Framework) and is derived from the DAML+OIL Web Ontology Language. This document contains a structured informal description of the full set of OWL language constructs and is meant to serve as a reference for OWL users who want to construct OWL ontologies.

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Abstract

We describe an apporach to retrieval of documents that consist of both free text and semantically enriched markup. In particular, we present the design and implementation prototype of a framework in which both documents and queries can be marked up with statements in the DAML+OIL semantic web language. These statement provide both structured and semi-structured information about the documents and their content. We claim that indexing text and semantic markup will significantly improve retrieval performance. Outr approach allows inferencing to be done over this information at several points: when a document is indexed,when a query is processed and when query results are evaluated.

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Abstract

This document specifies XML presentation syntax for OWL, which is defined as a dialect similar to OWL Abstract Syntax [OWL Semantics]. It is not intended to be a normative specification. Instead, it represents a suggestion of one possible XML presentation syntax for OWL.

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Abstract

This document specifies usage scenarios, goals and requirements for a web ontology language. An ontology formally defines a common set of terms that are used to describe and represent a domain. Ontologies can be used by automated tools to power advanced services such as more accurate web search, intelligent software agents and knowledge management.

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Content

"When dealing with a large-scale and widely-used knowledge organization system like the Dewey Decimal Classification, we often tend to focus solely on the organization aspect, which is closely intertwined with editorial work. This is perfectly understandable, since developing and updating the DDC, keeping up with current scientific developments, spotting new trends in both scholarly communication and popular publishing, and figuring out how to fit those patterns into the structure of the scheme are as intriguing as they are challenging. From the organization perspective, the intended user of the scheme is mainly the classifier. Dewey acts very much as a number-building engine, providing richly documented concepts to help with classification decisions. Since the Middle Ages, quasi-religious battles have been fought over the "valid" arrangement of places according to specific views of the world, as parodied by Jorge Luis Borges and others. Organizing knowledge has always been primarily an ontological activity; it is about putting the world into the classification. However, there is another side to this coin--the discovery side. While the hierarchical organization of the DDC establishes a default set of places and neighborhoods that is also visible in the physical manifestation of library shelves, this is just one set of relationships in the DDC. A KOS (Knowledge Organization System) becomes powerful by expressing those other relationships in a manner that not only collocates items in a physical place but in a knowledge space, and exposes those other relationships in ways beneficial and congenial to the unique perspective of an information seeker.
What are those "other" relationships that Dewey possesses and that seem so important to surface? Firstly, there is the relationship of concepts to resources. Dewey has been used for a long time, and over 200,000 numbers are assigned to information resources each year and added to WorldCat by the Library of Congress and the German National Library alone. Secondly, we have relationships between concepts in the scheme itself. Dewey provides a rich set of non-hierarchical relations, indicating other relevant and related subjects across disciplinary boundaries. Thirdly, perhaps most importantly, there is the relationship between the same concepts across different languages. Dewey has been translated extensively, and current versions are available in French, German, Hebrew, Italian, Spanish, and Vietnamese. Briefer representations of the top-three levels (the DDC Summaries) are available in several languages in the DeweyBrowser. This multilingual nature of the scheme allows searchers to access a broader range of resources or to switch the language of--and thus localize--subject metadata seamlessly. MelvilClass, a Dewey front-end developed by the German National Library for the German translation, could be used as a common interface to the DDC in any language, as it is built upon the standard DDC data format. It is not hard to give an example of the basic terminology of a class pulled together in a multilingual way: <class/794.8> a skos:Concept ; skos:notation "794.8"^^ddc:notation ; skos:prefLabel "Computer games"@en ; skos:prefLabel "Computerspiele"@de ; skos:prefLabel "Jeux sur ordinateur"@fr ; skos:prefLabel "Juegos por computador"@es .
Expressed in such manner, the Dewey number provides a language-independent representation of a Dewey concept, accompanied by language-dependent assertions about the concept. This information, identified by a URI, can be easily consumed by semantic web agents and used in various metadata scenarios. Fourthly, as we have seen, it is important to play well with others, i.e., establishing and maintaining relationships to other KOS and making the scheme available in different formats. As noted in the Dewey blog post "Tags and Dewey," since no single scheme is ever going to be the be-all, end-all solution for knowledge discovery, DDC concepts have been extensively mapped to other vocabularies and taxonomies, sometimes bridging them and acting as a backbone, sometimes using them as additional access vocabulary to be able to do more work "behind the scenes." To enable other applications and schemes to make use of those relationships, the full Dewey database is available in XML format; RDF-based formats and a web service are forthcoming. Pulling those relationships together under a common surface will be the next challenge going forward. In the semantic web community the concept of Linked Data (http://en.wikipedia.org/wiki/Linked_Data) currently receives some attention, with its emphasis on exposing and connecting data using technologies like URIs, HTTP and RDF to improve information discovery on the web. With its focus on relationships and discovery, it seems that Dewey will be well prepared to become part of this big linked data set. Now it is about putting the classification back into the world!"

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Abstract

18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.

Content

SKOS Adapts to the Diversity of Knowledge Organization Systems A useful starting point for understanding the role of SKOS is the set of subject headings published by the US Library of Congress (LOC) for categorizing books, videos, and other library resources. These headings can be used to broaden or narrow queries for discovering resources. For instance, one can narrow a query about books on "Chinese literature" to "Chinese drama," or further still to "Chinese children's plays." Library of Congress subject headings have evolved within a community of practice over a period of decades. By now publishing these subject headings in SKOS, the Library of Congress has made them available to the linked data community, which benefits from a time-tested set of concepts to re-use in their own data. This re-use adds value ("the network effect") to the collection. When people all over the Web re-use the same LOC concept for "Chinese drama," or a concept from some other vocabulary linked to it, this creates many new routes to the discovery of information, and increases the chances that relevant items will be found. As an example of mapping one vocabulary to another, a combined effort from the STITCH, TELplus and MACS Projects provides links between LOC concepts and RAMEAU, a collection of French subject headings used by the Bibliothèque Nationale de France and other institutions. SKOS can be used for subject headings but also many other approaches to organizing knowledge. Because different communities are comfortable with different organization schemes, SKOS is designed to port diverse knowledge organization systems to the Web. "Active participation from the library and information science community in the development of SKOS over the past seven years has been key to ensuring that SKOS meets a variety of needs," said Thomas Baker, co-chair of the Semantic Web Deployment Working Group, which published SKOS. "One goal in creating SKOS was to provide new uses for well-established knowledge organization systems by providing a bridge to the linked data cloud." SKOS is part of the Semantic Web technology stack. Like the Web Ontology Language (OWL), SKOS can be used to define vocabularies. But the two technologies were designed to meet different needs. SKOS is a simple language with just a few features, tuned for sharing and linking knowledge organization systems such as thesauri and classification schemes. OWL offers a general and powerful framework for knowledge representation, where additional "rigor" can afford additional benefits (for instance, business rule processing). To get started with SKOS, see the SKOS Primer.